"Information about Snowflake Data Warehouses" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
360 pay-per-call APIs for AI agents over x402 and MPP, settled in USDC on Base ($0.001-$0.25 a call, no account or API key). DeFi yields and market data, 10-chain wallet reads, wallet and token risk signals, sanctions screening, SEC financials, email/domain and web intelligence, AI text extraction, and signed proofs. Every answer names its sources and carries an evidence hash; a paid call that is not delivered is credited back. Built and run by UnyKorn LLC.
593 agent tools: chain data, prices, sanctions, web, PDF. 25 free calls, then from $0.002.
Read-only data on AI API relay stations: rank, purity, uptime, price per model.
25 tools: LLM chat, summaries, translation, embeddings, speech, images. 25 free calls.
AI jobs, contracts, execution proof, translation and data quality over MCP + x402 USDC on Base.
Refix is an AI analyst for company data. Ask business questions, analyze connected sources, set up watchers on ongoing goals, and catch up on findings from your AI assistant. Requires a Refix account and connected data sources. Connect with OAuth.
App Store Optimization data for AI agents: keyword ranks, scores, competitors, charts
Estimate what your company's operational data is worth to AI labs. Counts only, never content.
EasyGerber brings AI printed circuit board (PCB) design, layout, and routing to MCP-compatible assistants. Describe a circuit or start from firmware pin assignments, search published electronic components, and build schematics using catalog parts with their footprints and available 3D models. Create and revise boards, generate layouts with automatic component placement and routing, inspect previews, and check saved layouts for blocking design issues. Export manufacturing ZIPs containing Gerber and drill files, a bill of materials, and component placement data, or download an editable EasyGerber (.egb) file. Start without signing up. Your agent creates a private guest session for one board, including catalog access, edits, layout, checks, previews, and exports. Sign in through OAuth to work with saved account boards, access permitted organization boards, or save the guest design to your account. Guest support depends on your MCP client and installed integration.
Free, read-only directory of 114 AI trading tools: broker MCP servers, market data APIs, bots and backtesters. Sourced facts on who can place orders and what safeguards exist; search, compare and check order gating for every broker MCP.
Extract structured data from invoices, receipts, PDFs, scans, photos and emails. Create an inbox for a document type, define the fields and tables to extract (or propose a schema from a sample document), upload a document and get typed JSON back, review past documents, and add an optional Python post-processing step that is tested on a real document before it is enabled. 17 tools. Sign in with OAuth by pasting your Airparser API key (Account page of the Airparser app); the client only sees that account's inboxes and documents.
Veqen brings together work and coding agent costs per person and team, product inference costs per customer, agent spending, protection incidents, invoice checks, chargeback and the month-end close. Ask your assistant to investigate recorded spending, compare model prices, review provider keys and incidents, record bills and credits, or manage budgets, alerts, teams and spending policies. Your account role and plan govern access. Provider-key shut-off and agent-card controls require the appropriate role and provider permissions. Destructive actions require confirmation, and organizations can require a second person to approve a shut-off. SDK budget blocking is not a guaranteed spending cap. Work and coding agents are free for up to 3 people; product inference is free up to $1,000 in monthly AI spend. Connect your Veqen account for private organization data. The separate public model-price server needs no account. Estimates remain separate from provider invoices. Setup and permissions: https://veqen-app.com/docs/mcp
Ask about your business's sales, Google rankings, AI visibility and email marketing, and have Kooga write, change and send for you, asking first before anything leaves Kooga.
Ask Drex decision models typed questions about a state and get calibrated probabilities; free within per-network limits.
Ask how ten AI engines (ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews, AI Mode, Copilot, Grok, DeepSeek, Meta AI) describe a brand, which sources they cite and how that changed, then build white-label client reports from the same data. 74 tools; every write is shown as a preview first and needs a second, confirmed call.
# **RChilli** RChilli MCP Hub is a production-grade Model Context Protocol (MCP) server that exposes RChilli’s HR data intelligence platform through AI-callable tools. Built on 15+ years of HR data intelligence, RChilli supports ATS vendors, HR technology platforms, staffing agencies, and enterprise recruiting teams worldwide. The tools return consistent, structured JSON responses for recruiting, talent intelligence, skills, matching, compliance, and HR workflow use cases. `userkey` and `subuserid` are injected automatically from the Bearer token and must not be passed manually. <br> --- <br> # **Available Tools** <br> > ### **`analyze_hr_call`** > > Transcribes and analyzes HR or recruiting call recordings to extract speaker turns, sentiment, candidate intent, action items, skill mentions, and structured follow-up data for recruiting operations. <br> > ### **`analyze_skill_adjacency`** > > Identifies related, adjacent, and transferable skills to support skill discovery, talent mobility, workforce planning, and candidate evaluation. <br> > ### **`analyze_skill_gap`** > > Compares candidate or employee skills against a target job and returns present skills, missing skills, readiness score, and development areas for hiring, internal mobility, and workforce planning. <br> > ### **`autocomplete_job_profile`** > > Accepts a partial job title and returns ranked autocomplete suggestions with canonical titles and job families. Ensures job titles map to standardized taxonomy profiles from the moment a recruiter starts typing. <br> > ### **`autocomplete_skill`** > > Accepts a partial skill string and returns ranked autocomplete suggestions with canonical skill names and categories. Helps prevent free-text entry errors and keeps skill data clean. <br> > ### **`classify_job_zone`** > > Reads the job profile from a resume or job description and returns its O*NET Job Zone, from Zone 1 through Zone 5, based on the education, experience, and training preparation required for the role. <br> > ### **`convert_document_format`** > > Accepts a document as base64 or URL and converts between PDF, DOCX, RTF, HTML, and plain text. Useful as a pre-processing step before extracting data from non-standard document formats. <br> > ### **`detect_bias`** > > Reviews job descriptions and hiring criteria for gendered language, age-coded terms, unnecessary credential inflation, cultural exclusion signals, and related compliance risks. Suggests neutral replacements. <br> > ### **`detect_resume_suspicion`** > > Reviews candidate profile data for possible inconsistencies, unusual claims, timeline conflicts, missing context, and other signals that require recruiter review. <br> > ### **`extract_contacts`** > > Identifies and structures names, emails, phone numbers, LinkedIn URLs, and addresses with field-level confidence scores from candidate records, emails, or documents. <br> > ### **`extract_job_data`** > > Extracts and converts job descriptions into structured hiring data including job title, required skills, preferred skills, responsibilities, experience, education, and taxonomy-normalized role requirements. <br> > ### **`extract_resume_data`** > > Extracts and converts resumes, CVs, and candidate documents into structured, searchable profiles with contact details, skills, experience, education, certifications, and taxonomy-enriched data for ATS, HCM, and AI recruiting workflows. Supports multilingual extraction, batch processing, resume auto-fill, and reprocessing of historical resumes. <br> > ### **`extract_resume_data_from_url`** > > Accepts a direct URL to a PDF, DOCX, or RTF file and returns the same normalized JSON profile as Resume Data Extraction. Ideal for resumes stored in cloud storage, S3, email attachments, or other URL-accessible sources. <br> > ### **`find_matches_in_index`** > > Accepts a resume or job description as input and returns the top matching documents from the indexed corpus, ranked by semantic similarity. <br> > ### **`generate_interview_questions`** > > Creates technical, behavioral, situational, and competency-based interview questions tailored to a role and candidate profile, including question type, competency, and expected answer signals. <br> > ### **`generate_jd`** > > Generates structured job descriptions with title, responsibilities, required skills, preferred skills, qualifications, tone alignment, language support, and inclusivity scoring from role inputs. <br> > ### **`geolocate`** > > Converts partial or informal location text into structured city, state, country, ISO codes, latitude, and longitude. Supports radius-based candidate search and workforce planning. <br> > ### **`index_document`** > > Indexes a resume or job description in RChilli Search & Match so it can be searched, matched, updated, and reused across candidate matching, job matching, and similarity-search workflows. <br> > ### **`lookup_job_profile`** > > Returns authoritative detail for a known job profile including canonical title, SOC/O*NET code, job family, typical required and preferred skills, salary bands, and work context. <br> > ### **`lookup_skill`** > > Returns authoritative detail for a known skill including description, aliases, related skills, proficiency levels, and O*NET or ESCO mappings. <br> > ### **`map_job_to_skills`** > > Converts job descriptions into granular skill maps with required and preferred skill clusters, proficiency signals, taxonomy tags, and downstream matching attributes. <br> > ### **`match_end_to_end`** > > Orchestrates data extraction, indexing, taxonomy normalization, and matching to return ranked candidates or jobs with scores, explainable results, and an audit trail from a single call. <br> > ### **`normalize_candidate_data`** > > Cleans and normalizes candidate records from multiple ATS or HR systems, resolves field conflicts, deduplicates records, and produces standardized candidate data with a field-level change log. <br> > ### **`normalize_hr_data_with_lov`** > > Maps raw and inconsistent HR data values, including degrees, universities, certifications, job profiles, skills, and locations, to the closest configured List of Values entry with a standardized value and confidence score. <br> > ### **`recommend_learning_path`** > > Builds structured learning paths with prerequisites, skill sequence, certifications, proficiency targets, and LMS alignment based on a person’s profile and target role. <br> > ### **`redact_resume`** > > Redacts configured personally identifiable information from candidate profiles to support anonymized review, bias-aware screening, compliance workflows, and audit logs. <br> > ### **`reformat_resume_with_template`** > > Applies one of the RChilli resume templates, TM001 through TM006, to a structured candidate profile and produces a consistently formatted PDF, DOCX, RTF, or HTML document. <br> > ### **`score_resume_against_jd`** > > Accepts one resume and one job description and returns an overall match score, dimension scores, matched skills, skill gaps, and a natural-language explanation. No index is required. <br> > ### **`screen_application_batch`** > > Evaluates a batch of candidates against job requirements and custom criteria, returning scores, insights, skill gaps, and recommended next actions for each candidate. <br> > ### **`search_indexed_documents`** > > Accepts a query string and returns ranked document references from the tenant’s indexed corpus. Supports Boolean and semantic search modes. <br> > ### **`skill_mapping`** > > Maps raw skill text to standardized RChilli taxonomy skills, aliases, classifications, and related skill information. <br> > ### **`tag_entities`** > > Annotates extracted HR text by wrapping recognized entities in structured XML-style labels. Supported entities include job titles, skills, names, degrees, organizations, locations, countries, dates, and years.
90-day AI adoption framework for managers: overview, pricing, FAQ and an AI readiness assessment.
135 pay-per-call agent tools: agent intelligence, token risk, developer and AI data tools. x402
13 pay-per-call tools for AI agents: LLM chat, summaries, sentiment, classification, keywords, rewriting, outlines, translation, embeddings, JSON extraction, image generation, transcription and image description. USDC via x402.
A marketplace for AI agents. Tools and data for agents, on one MCP address. No account, no API key.
ChartGaze is a service that connects AI assistants to live and historical market data and, with your authorization, to trading-account information and trading actions. It works with MCP-compatible AI tools and supports platforms such as MT5, MT4, cTrader, and crypto exchanges.
Connect your health, fitness, nutrition, sleep, and wearable data to your AI assistant.
Veqen brings together work and coding agent costs per person and team, product inference costs per customer, agent spending, protection incidents, invoice checks, chargeback and the month-end close. Ask your assistant to investigate recorded spending, compare model prices, review provider keys and incidents, record bills and credits, or manage budgets, alerts, teams and spending policies. Your account role and plan govern access. Provider-key shut-off and agent-card controls require the appropriate role and provider permissions. Destructive actions require confirmation, and organizations can require a second person to approve a shut-off. SDK budget blocking is not a guaranteed spending cap. Work and coding agents are free for up to 3 people; product inference is free up to $1,000 in monthly AI spend. Connect your Veqen account for private organization data. The separate public model-price server needs no account. Estimates remain separate from provider invoices. Setup and permissions: https://veqen-app.com/docs/mcp
32 free MCP tools for data validation, text optimization, and synthetic test data.
AI visibility (GEO): how ChatGPT, Gemini and Google AI talk about your brand, with an action plan.
Axons Mobility is AI fleet management software with Intelligence and MCP. Ask about your scooter, bike, car sharing or golf cart fleet in Claude or ChatGPT. This public server answers product, pricing and trial questions with 3 help tools (no sign-in). Inside your own workspace, MCP gives 40+ fleet tools with role-based access, and nothing changes until a person confirms. https://axonsmobility.com
Search and preview datasets publicly. Account-required full data via MCP.
Remote MCP server exposing 330 production AI-agent services for web/data processing, validation, AI utilities, blockchain/crypto utilities, and x402 pay-per-use access.
Track what people say about your product on Reddit, X, Hacker News, GitHub and more
MarketCode is an AI-powered UK property intelligence platform by RoboSapien Limited. Its flagship agentic AI valuation pairs a free AVM estimate with a £20 AI-researched valuation report, sources and comparables behind every number. Its Analyst agent plans research, cross-checks evidence and returns sourced answers, shortlists and reports. Land Registry sales, listings, planning and title data - all on one map. REST API and MCP server included.
